Solutions
Synthetic Biology
Synthetic biology closes a loop between design and experiment. UVJ builds the software that carries a design through to a verified result, and the data back again.
Overview
What it is
Synthetic biology applies engineering principles to biological systems: designing genetic constructs and biological parts, building them in the laboratory, testing them, and learning from the result. The software layer connects design tools, laboratory automation, instrumentation and data analysis into a coherent design-build-test-learn cycle.
The problem
Problems we solve
- Design intent lost in the handoff to laboratory execution
- Laboratory steps that are manual, hard to reproduce and slow to scale
- Build and test data that cannot be linked back to the construct it came from
- Instruments and design tools that do not exchange structured data
- Strain and part libraries managed in files rather than a queryable system
Capabilities
What we build
Construct, part and strain data management
Design-build-test-learn workflow orchestration
Laboratory automation and instrument integration
Data capture, analysis and experiment tracking
Laboratory information systems for strain and sample lineage
AI-assisted design and experimental prioritisation
Toolkit
Technologies & capabilities
- Workflow orchestration and laboratory scheduling
- Instrument adapters and device communication
- Structured biological data models
- Python and R analysis stacks
- Cloud and edge deployment for instrument control
Who it is for
Designed for
- Synthetic biology and metabolic engineering groups
- Industrial biotechnology and bio-based materials companies
- Academic and translational research laboratories
- Biofoundries and central automation facilities
Why UVJ
Why teams choose UVJ for this
We connect design to execution
Our strength is the integration layer between design tools, instruments and data, so a construct can be traced from intention to verified result.
Automation and software together
We combine laboratory automation, instrument software and data engineering rather than treating them as separate projects.
Built for iteration
The design-build-test-learn cycle only works at speed if the software supports rapid, traceable iteration. We build for exactly that.
FAQ
Frequently asked questions
Do you build the automation hardware as well as the software?
Our core focus is software and firmware: instrument control, adapters, workflow orchestration and data systems. We frequently integrate with existing liquid-handling and laboratory automation hardware rather than replacing it.
How is experiment lineage handled?
We model constructs, parts, samples and experiments as connected entities with recorded lineage, so any result can be traced back through the steps and inputs that produced it.
Can AI support construct or experiment design?
Yes, where it adds measurable value. We apply machine learning to prioritise candidates, detect patterns and guide experimental design, while keeping scientists in control of the decision.
Related solutions
Laboratory Automation
Software, firmware, instrument integration and data pipelines that turn manual laboratory workflows into reliable, high-throughput systems.
Learn moreBioinformatics
Pipeline engineering, analysis tooling and scalable data platforms for genomic, transcriptomic and multi-omic research.
Learn moreScientific Software
Custom software for instruments, scientific workflows and regulated research environments — built to be validated, auditable and maintainable for years.
Learn moreLet's engineer what's next.
Tell us about the problem. You will speak with an engineer who understands the domain, not a call centre.